Dataset Information

Prognostic potential of lncRNA RHPN1-AS1 in glioma.

ABSTRACT: Expression level of long non-coding RNA (lncRNA) RHPN1-AS1 in glioma tissues was detected to determine potential risk factors influencing prognosis of glioma. This study aimed to clarify the molecular mechanisms underlying tumorigenesis of glioma and thus to improve therapeutic efficacy of glioma. RHPN1-AS1 levels in glioma tissues (n=105) and normal brain tissues (n=105) were detected by quantitative real-time polymerase chain reaction (qRT-PCR). The relationship between RHPN1-AS1 level and pathological indicators of glioma patients was analyzed. Glioma patients were followed up for 5 years. Overall survival (OS) and relapse-free survival (RFS) in glioma patients were tested by Kaplan-Meier and log-rank method. Potential factors influencing prognosis of glioma were analyzed by Cox regression model. RHPN1-AS1 was upregulated in glioma tissues. Its level was correlated to histological grade, Karnofsky (KPS) score and postoperative recurrence of glioma patients, rather than sex, age, pathological and tumor size. Glioma patients expressing high level of RHPN1-AS1 suffered worse OS and RFS than those with low level. Advanced histological grade, KPS score <80 and high level of RHPN1-AS1 were considered to be risk factors influencing postoperative prognosis of glioma. High level of RHPN1-AS1 is an independent risk factor for poor prognosis of glioma, which may be utilized as a prognostic hallmark.

SUBMITTER: Wu Y

PROVIDER: S-EPMC7400277 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Prognostic potential of lncRNA RHPN1-AS1 in glioma.

Wu Yong Y Wei Wuting W Tang Linjun L Wang Liangwei L

Oncology letters 20200625 3

Expression level of long non-coding RNA (lncRNA) RHPN1-AS1 in glioma tissues was detected to determine potential risk factors influencing prognosis of glioma. This study aimed to clarify the molecular mechanisms underlying tumorigenesis of glioma and thus to improve therapeutic efficacy of glioma. RHPN1-AS1 levels in glioma tissues (n=105) and normal brain tissues (n=105) were detected by quantitative real-time polymerase chain reaction (qRT-PCR). The relationship between RHPN1-AS1 level and pat ...[more]

PMID: 32782561

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Project description:Background: Knowledge about the prognostic role of long noncoding RNA (lncRNA) in colorectal cancer (CRC) is limited. Therefore, we constructed a lncRNA-related prognostic model based on data from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). Materials and Methods: CRC transcriptome and clinical data were downloaded from the GSE20916 dataset and the TCGA database, respectively. R software was used for data processing and analysis. The differential lncRNA expression within the two datasets was first screened, and then intersections were measured. Cox regression and the Kaplan-Meier method were used to evaluate the effects of various factors on prognosis. The area under the curve (AUC) of the receiver operating characteristic curve and a nomogram based on multivariate Cox analysis were used to estimate the prognostic value of the lncRNA-related model. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were applied to elucidate the significantly involved biological functions and pathways. Results: A total of 11 lncRNAs were crossed. The univariate Cox analysis screened out two lncRNAs, which were analyzed in the multivariate Cox analysis. A nomogram based on the two lncRNAs and other clinicopathological risk factors was constructed. The AUC of the nomogram was 0.56 at 3 years and 0.71 at 5 years. The 3-year nomogram model was compared with the ideal model, which showed that some indices of the 3-year model were consistent with the ideal model, suggesting that our model was highly accurate. The GO and KEGG enrichment analyses showed that positive regulation of secretion by cells, positive regulation of secretion, positive regulation of exocytosis, endocytosis, and the calcium signaling pathway were differentially enriched in the two-lncRNA-associated phenotype. Conclusions: A two-lncRNA prognostic model of CRC was constructed by bioinformatics analysis. The model had moderate prediction accuracy. LncRNA BBOX1-AS1 and lncRNA FOXP4-AS1 were identified as prognostic biomarkers.

Project description:Background Ovarian cancer (OvCa) is a malignant disease of the female reproductive system with a high mortality rate. LncRNA has been confirmed to play a crucial role in the development and progression of various cancer types. Novel lncRNA ZFHX4-AS1 has been reported in several cancers, albeit its functional mechanisms in OvCa remain unclear. Methods With reference to the public databases and based on integrating bioinformatics analyses, we explored the expression of ZFHX4-AS1 and its roles in the prognosis of OvCa. We employed the Kaplan-Meier curves to investigate the outcome of patients with different ZFHX4-AS1 expressions. Furthermore, its biological function and the related hallmark pathways were assessed through Gene Ontology (GO) annotation, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, and Gene-set enrichment analysis (GSEA). We explored the correlation between lncRNA ZFHX4-AS1 and tumor-infiltrating immune cells through CIBERSORT. The immune checkpoints associated with lncRNA ZFHX4-AS1 and its related genes were investigated. The effect of lncRNA ZFHX4-AS1 on proliferation, invasion and migration of OvCa cells was verified through Cell Counting Kit (CCK)-8, colony formation, wound healing and transwell assays. Results The expression of lncRNA ZFHX4-AS1 was upregulated in OvCa relative to that in normal tissues. Increased lncRNA ZFHX4-AS1 expression was associated with poor overall survival and progression-free survival in OvCa. The GO and KEGG pathway analyses revealed the role of lncRNA ZFHX4-AS1 in cell metabolism, protein synthesis, cell proliferation, and cell cycle. GSEA indicated the hallmark gene sets that were significantly enriched in the high and low expression groups. The CIBERSORT database revealed M2 macrophages, memory B-cells, naïve B cells, and activated NK cells were affected by lncRNA ZFHX4-AS1 expression (all P < 0.05). The expression of lncRNA ZFHX4-AS1 and its related differential genes MRPS11, NSA2, and MRPL13 were significantly correlated with the immune checkpoints. Knockdown of lncRNA ZFHX4-AS1 could inhibit the proliferation, invasion and migration of OvCa cells. Conclusions The results suggested that lncRNA ZFHX4-AS1 is a novel prognostic biomarker associated with cell proliferation, metabolism, infiltration, and distribution of tumor-infiltrating immune cells in OvCa, indicating that lncRNA ZFHX4-AS1 can be used as a potential therapeutic target for OvCa in the future.

Dataset Information

Prognostic potential of lncRNA RHPN1-AS1 in glioma.

Publications

Prognostic potential of lncRNA RHPN1-AS1 in glioma.

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